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DOI	10.1016/j.agwat.2020.106226
	A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels
	Uddameri, Venkatesh; Ghaseminejad, Ali; Hernandez, E. Annette
通讯作者	Uddameri, V
来源期刊	AGRICULTURAL WATER MANAGEMENT
ISSN	0378-3774
EISSN	1873-2283
出版年	2020
卷号	238
英文摘要	Agricultural production in arid and semi-arid regions is threatened by increased droughts (climate change) and groundwater depletion. Farmers increasingly must weigh the short-term economic gains from irrigation against the long-term aquifer longevity needs. Risk-based deficit irrigation is proposed to tackle this trade-off. A tiered risk assessment approach is developed to evaluate crop yield loss risks as a function of crop water supply (CWS) from irrigation and precipitation. Risk is defined as the probability of obtaining a crop yield below a pre-specified threshold. Logistic regression is used to quantify risks as a function of CWS, if the producer can specify a fixed minimum yield threshold. Distribution regression is used to develop the cumulative distribution function of the crop yield assuming heterogeneous model parameter and is useful when the producer can estimate CWS but cannot specify a minimum yield threshold. Finally, the CWS is also modeled as a stochastic variable and the crop yield risk conditioned on CWS risk is computed using the Kolmogorov axiom. The methodology is illustrated using a cotton production case-study in the Southern High Plains of Texas. Logistic regression indicated that crop yield risk was a nonlinear function of CWS. CWS corresponding to similar to 80 % of the total crop water demand was enough to reach negligible crop yield risks. Heterogeneous cotton yield distribution was modeled using Box-Cox-Cole-Green function with location and scale parameters being nonlinear and linear functions of CWS respectively and a stationary shape parameter. Irrigation at lower CWS reduced the risks substantially but the risk reductions were marginal at higher CWS. The conditional distribution of crop yield risk indicated that CWS corresponding to similar to 80 %-85 % of crop water demand was enough to bring down risks. The tiered risk assessment provides a rational risk-based approach to evaluate the impacts of crop water supply reductions and promote deficit irrigation practices.
英文关键词	Droughts: aquifer depletion Deficit irrigation Distribution regression Kernel density estimation Crop yield risks Climate change Probabilistic risk assessment
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000536054500007
WOS关键词	FLOOD FREQUENCY-ANALYSIS ; CLIMATE-CHANGE ; DEFICIT IRRIGATION ; PROBABILISTIC EVALUATION ; BANDWIDTH SELECTION ; CENTILE CURVES ; COTTON MODEL ; HIGH-PLAINS ; GROUNDWATER ; MANAGEMENT
WOS类目	Agronomy ; Water Resources
WOS研究方向	Agriculture ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/324559
作者单位	[Uddameri, Venkatesh; Ghaseminejad, Ali; Hernandez, E. Annette] Texas Tech Univ, Dept Civil Environm & Construct Engn, Lubbock, TX 79409 USA
推荐引用方式 GB/T 7714	Uddameri, Venkatesh,Ghaseminejad, Ali,Hernandez, E. Annette. A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels[J],2020,238.
APA	Uddameri, Venkatesh,Ghaseminejad, Ali,&Hernandez, E. Annette.(2020).A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels.AGRICULTURAL WATER MANAGEMENT,238.
MLA	Uddameri, Venkatesh,et al."A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels".AGRICULTURAL WATER MANAGEMENT 238(2020).